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Autonomous vehicles are entering daily life, with driverless taxis such as Waymo's set to arrive in London in 2026. Yet a critical question remains unanswered: how will an 80-year-old or disabled pedestrian know when it's safe to cross in front of a car with no driver? The PedICAV project addresses this gap by studying how disabled and older pedestrians perceive safety and make crossing decisions when interacting with Connected and Autonomous Vehicles (CAVs), with the aim of supporting a safe and inclusive rollout of autonomous mobility.

Using a novel Virtual Reality framework alongside stated preference surveys, the project safely observes the hypothetical road-crossing behaviours of disabled and older pedestrians under a wide range of CAV conditions. This VR data will be validated against real-world observations from the Smart Mobility Living Lab (SMLL), ensuring the behaviours captured in simulation genuinely reflect real-world patterns. By analysing both discrete decisions (whether to cross) and continuous responses (such as changes in walking speed), the research builds an evidence base linking specific CAV designs and communication strategies to pedestrians' sense of safety.

The project's outputs include a policy-ready evidence base to inform vehicle design, infrastructure planning and regulation, an openly available dataset of detailed VR crossing behaviour, and an assessment of VR's value as a tool for testing the safety of new AV control systems.

PedICAV is led by the Urban Systems Lab in the Department of Civil and Environmental Engineering at ÌìÃÀ´«Ã½, funded by the Road Safety Trust, and delivered with collaborators RiDC and SMLL, supported by an advisory board spanning industry, government and academia. The project aims to help build a future of autonomous mobility that is not only intelligent but genuinely inclusive, where every pedestrian, regardless of age or ability, can cross the road safely.